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Higher concentrations of ambient air pollutants, including PM2.5 and NO2, and other pollutants have been found near active oil and gas wells and may be associated with adverse COVID‐19 outcomes. We assessed whether residential exposure to nearby oil and gas production was associated with higher rates of the respiratory infection COVID‐19 and related mortality using a population‐based ecological study in California. Using gridded population estimates, we estimated area‐level exposure to annual average oil and gas production volume from active wells within 1 kilometer (km) of populated areas within census block groups from 2018 to 2020. We geocoded confirmed cases and associated deaths to assess block group case and mortality rates from COVID‐19 from February 2020 to January 2021. We fit hierarchical Poisson models with individual and area covariates (e.g., age, sex, socioeconomic disadvantage), and included time and other interactions to assess additional variation (e.g., testing, reporting rates). In the first 4 months of the study period (February–May 2020), block groups in the highest tertile of oil and gas production exposure had 34% higher case rates (IRR: 1.34 95% CI: 1.20, 1.49) and 55% higher mortality rates (MRR: 1.52 95%: CI: 1.14, 2.03) than those with no estimated production, after accounting for area‐level covariates. Over the entire study period, we observed moderately higher mortality rates in the highest group (MRR: 1.16 95%: CI: 1.01, 1.33) and null associations for case rates. Plain Language Summary: Exposure to air, noise, light pollution and other localized stressors from active oil and gas drilling may affect the immune and cardiovascular systems and respiratory health, including diseases such as COVID‐19. This study reports on COVID‐19 case and death rates in communities within 10 km of active oil and gas production. We observed that California communities that were located less than 1 km from an actively producing oil and gas well were more likely to have higher COVID‐19 case and death rates in the first 4 months of the pandemic, especially when the level of production was high. Across our entire study time (February 2020–January 2021), we did not observe higher rates of cases or deaths in these communities, except for deaths in communities with the highest amount of production. These results suggest that if there is an effect of oil and gas production on COVID‐19 rates, it may be on the number of people that become severely ill; overall, it suggests that more research may help to understand why different communities had different levels of COVID‐19. Key Points: Using gridded population estimates, we estimated exposure to oil and gas production in areas within 1 km of an active wellWe observed higher reported case and mortality rates in areas with higher estimated oil and gas production from February to May 2020We geocoded COVID‐19 cases and deaths to census block groups and estimated age and sex‐specific mortality rates from February 2020 to January 2021 [ABSTRACT FROM AUTHOR]

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 > 5 µg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (= 2 consecutive days with > 15 µg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups. [ABSTRACT FROM AUTHOR]

BACKGROUND: Increasingly, marginalized communities are disproportionately facing the worsening effects of environmental hazards, including air pollution, water pollution, and climate change. Language isolation and accessibility has been understudied as a determinant of health. Spanish, despite being the second-most common language in the United States with some 41.8 million speakers, has been neglected among environmental health scientists. Building capacity in high-quality Spanish-language science communication, both for scientific and nonscientific audiences, can yield improvements in health disparities research, public health literacy, international collaborations, and diversity and inclusion efforts. OBJECTIVES: In this article, we discuss the context of language diversity in environmental health sciences and offer recommendations for improving science communication in Spanish. DISCUSSION: English is currently the predominant language for scientific discourse, but Spanish and other non-English languages are routinely used by many environmental health science students and professionals, as well as much of the public. To more effectively conduct and communicate environmental health work in Spanish, we suggest that researchers and scientific institutions a) foster structural changes, b) train emerging scholars and support established researchers, c) tap into community ways of knowing, and d) leverage emerging technologies. [ABSTRACT FROM AUTHOR]

People living near oil and gas development are exposed to multiple environmental stressors that pose health risks. Some studies suggest these risks are higher for racially and socioeconomically marginalized people, which may be partly attributable to disparities in exposures. We examined whether racially and socioeconomically marginalized people in California are disproportionately exposed to oil and gas wells and associated hazards. We longitudinally assessed exposure to wells during three time periods (2005–2009, 2010–2014, and 2015–2019) using sociodemographic data at the census block group‐level. For each block group and time period, we assessed exposure to new, active, retired, and plugged wells, and cumulative production volume. We calculated risk ratios to determine whether marginalized people disproportionately resided near wells (within 1 km). Averaged across the three time periods, we estimated that 1.1 million Californians (3.0%) lived within 1 km of active wells. Nearly 9 million Californians (22.9%) lived within 1 km of plugged wells. The proportion of Black residents near active wells was 42%–49% higher than the proportion of Black residents across California, and the proportion of Hispanic residents near active wells was 4%–13% higher than their statewide proportion. Disparities were greatest in areas with the highest oil and gas production, where the proportion of Black residents was 105%–139% higher than statewide. Socioeconomically marginalized residents also had disproportionately high exposure to wells. Though oil and gas production has declined in California, marginalized communities persistently had disproportionately high exposure to wells, potentially contributing to health disparities. Plain Language Summary: People living near oil and gas wells are exposed to pollutants that may adversely affect their health. We investigated whether racially or socioeconomically marginalized people in California had disproportionately higher exposure to wells. We also assessed whether disparities were wider in areas with more intensive oil and gas production. We examined changes in neighborhood‐level sociodemographic characteristics in three time periods: 2005–2009, 2010–2014, and 2015–2019. For each neighborhood and time period, we estimated the number of wells and the total volume of oil and gas produced within 1 km (0.62 miles). We estimated that approximately 1.1 million Californians (3.0%) lived within 1 km of active wells between 2005 and 2019. The proportion of Black residents living near active wells was 42%–49% higher than the proportion of Black residents across California, and the proportion of Latinx residents near active wells was 4%–13% higher than their statewide proportion. For Black people, the disparities were widest in Los Angeles County neighborhoods with the most intensive production. Socioeconomically marginalized people also had disproportionately high exposure. Most disparities persisted throughout the 15‐year study period. Black, Hispanic, and socioeconomically marginalized people had disproportionately high exposure to wells, potentially contributing to health disparities. Key Points: Black, Hispanic, and socioeconomically marginalized people persistently had disproportionately high exposure to oil and gas developmentThe widest observed disparities were for Black people residing in neighborhoods with the most intensive oil and gas productionDisparities in exposure to oil and gas development may contribute to previously reported health disparities [ABSTRACT FROM AUTHOR]

Understanding effects of extreme heat across diverse settings is critical as social determinants play an important role in modifying heat-related risks. We apply a multi-scale analysis to understand spatial variation in the effects of heat across Mexico and explore factors that are explaining heterogeneity. Daily all-cause mortality was collected from the Mexican Secretary of Health and municipality-specific extreme heat events were estimated using population-weighted temperatures from 1998 to 2019 using Daymet and WorldPop datasets. We analyzed the association between single-day extreme heat events defined at the 99th percentile of the same-day maximum temperature and mortality, and seven heat threshold metrics based on relative and absolute scales were considered as sensitivity analyses. A time-stratified case-crossover was applied to evaluate heat impacts across 32 states in Mexico. A within-community matched design with Bayesian Hierarchical model explored effects across 2456 municipalities. A random-effects meta-regression was applied to understand which municipality-level socio-demographic characteristics such as education, age and housing predicted observed spatial heterogeneity. Extreme heat increased the odds of mortality overall, and this was consistent across extreme heat thresholds. At the state level, extreme heat events showed highest impact on mortality in Tabasco [OR: 1.23, 95% CI: 1.17, 1.30]. The municipality-level spatial analysis showed substantial differences across regions with highest effects observed along the eastern, southwestern and Sonora coasts. Municipalities with older populations, higher marginalization, lower education, and poorer housing conditions were more vulnerable to heat effects. Understanding the differential risks of extreme heat events at varying scales is important to prioritize at-risk populations in action plans and policies to reduce their burden., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The western United States is home to most of the nation's oil and gas production and, increasingly, wildfires. We examined historical threats of wildfires for oil and gas wells, the extent to which wildfires are projected to threaten wells as climate change progresses, and exposure of human populations to these wells. From 1984-2019, we found that cumulatively 102,882 wells were located in wildfire burn areas, and 348,853 people were exposed (resided ≤ 1 km). During this period, we observed a five-fold increase in the number of wells in wildfire burn areas and a doubling of the population within 1 km of these wells. These trends are projected to increase by late century, likely threatening human health. Approximately 2.9 million people reside within 1 km of wells in areas with high wildfire risk, and Asian, Black, Hispanic, and Native American people have disproportionately high exposure to wildfire-threatened wells., Competing Interests: Declaration of Interests. The authors declare no competing interests.

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM 2.5 ) concentrations differ from relatively smoothly varying total PM 2.5 . Thus, we introduced a conceptual model for computing long-term wildfire PM 2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM 2.5 exposure based on intermittent and extreme daily wildfire PM 2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM 2.5 < 5 μg/m 3 ; 2) days with non-zero wildfire PM 2.5 ; 3) mean wildfire PM 2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with <15 μg/m 3 wildfire PM 2.5 ); and 5) mean annual wildfire PM 2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM 2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM 2.5 exposure for several racial/ethnic groups., Competing Interests: Competing interests statement:The authors declare no competing interest.

Purpose of Review: The volume of public health environmental justice (EJ) research produced by academic institutions increased through 2022. However, the methods used for evaluating EJ in exposure science and epidemiologic studies have not been catalogued. Here, we completed a scoping review of EJ studies published in 19 environmental science and epidemiologic journals from 2018 to 2021 to summarize research types, frameworks, and methods., Recent Findings: We identified 402 articles that included populations with health disparities as a part of EJ research question and met other inclusion criteria. Most studies (60%) evaluated EJ questions related to socioeconomic status (SES) or race/ethnicity. EJ studies took place in 69 countries, led by the US (n = 246 [61%]). Only 50% of studies explicitly described a theoretical EJ framework in the background, methods, or discussion and just 10% explicitly stated a framework in all three sections. Among exposure studies, the most common area-level exposure was air pollution (40%), whereas chemicals predominated personal exposure studies (35%). Overall, the most common method used for exposure-only EJ analyses was main effect regression modeling (50%); for epidemiologic studies the most common method was effect modification (58%), where an analysis evaluated a health disparity variable as an effect modifier. Based on the results of this scoping review, current methods in public health EJ studies could be bolstered by integrating expertise from other fields (e.g., sociology), conducting community-based participatory research and intervention studies, and using more rigorous, theory-based, and solution-oriented statistical research methods., (© 2023. The Author(s).)

Background: Increasingly, marginalized communities are disproportionately facing the worsening effects of environmental hazards, including air pollution, water pollution, and climate change. Language isolation and accessibility has been understudied as a determinant of health. Spanish, despite being the second-most common language in the United States with some 41.8 million speakers, has been neglected among environmental health scientists. Building capacity in high-quality Spanish-language science communication, both for scientific and nonscientific audiences, can yield improvements in health disparities research, public health literacy, international collaborations, and diversity and inclusion efforts., Objectives: In this article, we discuss the context of language diversity in environmental health sciences and offer recommendations for improving science communication in Spanish., Discussion: English is currently the predominant language for scientific discourse, but Spanish and other non-English languages are routinely used by many environmental health science students and professionals, as well as much of the public. To more effectively conduct and communicate environmental health work in Spanish, we suggest that researchers and scientific institutions a ) foster structural changes, b ) train emerging scholars and support established researchers, c ) tap into community ways of knowing, and d ) leverage emerging technologies. https://doi.org/10.1289/EHP12306.